Triple
T38274900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Callcott |
E1021917
|
entity |
| Predicate | hasRelationshipToSetting |
P44691
|
FINISHED |
| Object | European expatriate in Australia |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: European expatriate in Australia | Statement: [Jack Callcott, hasRelationshipToSetting, European expatriate in Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipToSetting Context triple: [Jack Callcott, hasRelationshipToSetting, European expatriate in Australia]
-
A.
associatedWithSetting
chosen
Indicates that one entity is connected or linked to a particular context, environment, or setting in which it occurs or is relevant.
-
B.
hasSettingBy
Indicates that something (such as a work, event, or scenario) has its contextual environment, location, or background defined or established by a particular agent or source.
-
C.
hasSettingRole
Indicates that an entity participates in a setting by fulfilling a specific contextual or functional role within it.
-
D.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
E.
hasRelationships
Indicates that an entity is connected to one or more other entities through specified types of relationships.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.